Managing moving objects databases with uncertainty

This work addresses the problem of managing moving objects databases which capture the inherent uncertainty associated with the location of moving point objects. We address the issues of: (1) modeling and constructing the trajectories based on the information available in electronic maps. The proposed model of the trajectory captures all of the temporal, spatial and uncertainty aspects; (2)  simplification/reduction of the trajectories' representation in order to save storage space, as well as improve the querying performance; (3) updating the database based on the real-time information about traffic abnormalities; (4) the uncertainty aspect in the trajectory model; (5) querying a trajectories database with uncertainty; and (6) triggers utilization in maintaining the consistency of the answer-set for users' queries to the moving objects database.; The trajectory is modeled as a 3D cylindrical body. The model incorporates uncertainty in a manner that enables efficient querying. Thus, our model strikes a balance between modeling power and computational efficiency. To demonstrate efficiency, we report on experimental results that relate the length of a trajectory to its size in bytes. We have generated a real data-set of over 1000 trajectories, based on the maps of 18 counties around Chicago metropolitan area, which was used in our experiments.; We introduce a set of novel but natural spatio-temporal operators which capture uncertainty, and are used to express spatio-temporal range queries. We also devise and analyze algorithms to process these operators which, as it turned out, have strong “computational geometry flavor”. The operators have been implemented as a part of the DOMINO project conducted at the Database and Mobile Computing Laboratory (DBMC) at the University of Illinois at Chicago.